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Prediction of Climate Change Using Statistical Downscaling Techniques

  • Souranshu Prasad SahooEmail author
  • Kanhu Charan Panda
Chapter
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Abstract

Climate change is a burning issue in today’s world. Its effects are being seen in every corner of the world. Hence, measures are needed to neutralise its effects. The first step towards its mitigation would be the prediction of climate scenario for the future. Till now, one of the best methods we have to predict future climate scenario is the downscaling method. This chapter deals with various methods of downscaling and focuses mainly on statistical downscaling. This downscaling technique is a very new area of study and is in its infant stage. The statistical downscaling is very simple as compared to other downscaling methods. We have various climate models available known as general circulation models (GCM), which simulate coarse resolution climate variables for both present and future over the Earth. But the model cannot simulate fine resolution variables of hydrologic interest for a small area. The statistical downscaling technique links the coarse resolution GCM predictors with the observed hydrologic parameters statistically and develops a relation, which is used to project the hydrologic parameters into the future using the GCM scenarios. The method gives an idea about the future climate and is not accurate. Hence, a lot of research and development work is still needed.

Keywords

Statistical downscaling GCM Climate change Climate model Weather generators 

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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Farm Engineering, Institute of Agricultural SciencesBanaras Hindu UniversityVaranasiIndia

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